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A Parallel Processing Scheme for big data targeting a computer with many CPU cores and a large capacity main memory.

Research Project

Project/Area Number 15K12006
Research Category

Grant-in-Aid for Challenging Exploratory Research

Allocation TypeMulti-year Fund
Research Field Software
Research InstitutionUniversity of Tsukuba

Principal Investigator

KATO kazuhiko  筑波大学, システム情報系, 教授 (90224493)

Co-Investigator(Kenkyū-buntansha) 阿部 洋丈  筑波大学, システム情報系, 准教授 (00456716)
長谷部 浩二  筑波大学, システム情報系, 助教 (80470045)
Project Period (FY) 2015-04-01 – 2017-03-31
Project Status Completed (Fiscal Year 2016)
Budget Amount *help
¥3,380,000 (Direct Cost: ¥2,600,000、Indirect Cost: ¥780,000)
Fiscal Year 2016: ¥1,690,000 (Direct Cost: ¥1,300,000、Indirect Cost: ¥390,000)
Fiscal Year 2015: ¥1,690,000 (Direct Cost: ¥1,300,000、Indirect Cost: ¥390,000)
Keywordsビッグデータ / メニーコア / 並列処理 / B木 / B+木 / マルチスレッド / 代数的構造
Outline of Final Research Achievements

We have conducted research and development on a high-speed processing method for big data processing targeting a computer with many CPU cores and a large capacity main memory. Many of useful big data processing has mathematical properties to derive parallelism. By using that, we proposed a parallel processing scheme to data partition and processing, and the intermediate results are merged in an almost lock-free manner, which enables full-parallelism. We implemented the scheme using the Scala programming language. We conducted experiments using real machines and confirmed that high-speed big data parallel processing can be performed efficiently with the scheme.

Report

(3 results)
  • 2016 Annual Research Report   Final Research Report ( PDF )
  • 2015 Research-status Report
  • Research Products

    (3 results)

All 2016 2015

All Journal Article (3 results) (of which Peer Reviewed: 2 results)

  • [Journal Article] メニーコアマシン環境における並列B木マージを利用したビッグデータ処理方式の検討2016

    • Author(s)
      天沼 駿亮,鷹野 駿介,加藤 和彦,阿部 洋丈
    • Journal Title

      日本ソフトウェア科学会第32回大会

      Volume: 32 Pages: 1-7

    • NAID

      40020657408

    • Related Report
      2016 Annual Research Report
  • [Journal Article] A Game Theoretic Approach to Power Reduction in Distributed Storage Systems2016

    • Author(s)
      Koji Hasebe, Takumi Sawada, and Kazuhiko Kato
    • Journal Title

      Journal of Information Processing

      Volume: 24 Issue: 1 Pages: 173-181

    • DOI

      10.2197/ipsjjip.24.173

    • NAID

      130005119985

    • ISSN
      1882-6652
    • Related Report
      2015 Research-status Report
    • Peer Reviewed
  • [Journal Article] Power-Saving in Storage Systems for Cloud Data Sharing Services with Data Access Prediction2015

    • Author(s)
      Koji Hasebe, unpei. Okoshi, and Kazuhiko Kato
    • Journal Title

      IEICE Transactions on Information and Systems

      Volume: E98.D Issue: 10 Pages: 1744-1754

    • DOI

      10.1587/transinf.2014EDP7421

    • NAID

      130005101299

    • ISSN
      0916-8532, 1745-1361
    • Related Report
      2015 Research-status Report
    • Peer Reviewed

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Published: 2015-04-16   Modified: 2018-03-22  

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